Development of a fuzzy logic based model for HIV risk analysis and prediction

Abstract

Human Immunodeficiency Virus (HIV) risk analysis and prediction is crucial to effective decision making in sensitizing and providing appropriate support to the population of people in an area. Previous works on applicability of fuzzy logic to HIV analysis and prediction built their models on diagnostic and clinical data of few people who voluntarily submitted themselves for HIV screening test. Besides, most risk factors emanating from socio-cultural, attitudinal, behavioural, and demographic data were not considered in the previous studies. These made the models to have poor analysis and prediction capabilities. This study therefore, aimed at designing a specific HIV risk analysis and prediction model with better prediction capability. The proposed model was designed considering socio-cultural, clinical, behavioural, attitudinal and demographic risk factors relating to HIV risk and the knowledge obtained from experts of Virology Department of Obafemi Awolowo University Teaching Hospital (OAUTHC). Research data were collected majorly on HIV from experts and through a google questionnaire sent to individuals and various groups. Fuzzy logic toolbox in MATLAB 2018b and triangular membership function were used to model the proposed system. The results from the study showed that the model developed is reliable in analyzing and predicting HIV risk level of individuals and population of people in an area for effective decision making. In conclusion, the model developed in the study produced a viable tool for HIV analysis and prediction with a linguistic interpretation feature, reliable analysis and prediction capabilities.